Solutions

PNNL's technologies have been applied to solve a variety of analytics problems, such as calculating contingencies for power grid operations, identifying malicious cyber activity in large networks, and visualizing themes and relationships in libraries of text documents. The size, velocity, and/or complexity of today's data often makes it difficult to gain clarity and extract value. However, by combining profound knowledge regarding the domain and creative integration of advanced hardware and software, PNNL can deliver unique solutions to meet our clients’ needs.

Below are some examples of the real-world problems our customers face and how our technologies provide solutions to those problems.

Power Grid Contingency Analysis

Preventing power outages using a deeper understanding of contingency analysis

Utilities are required by regulatory agencies to operate their grids so that instability, uncontrolled separation, or cascading outages will not occur as a result of the most severe single contingency and specified multiple contingencies. Today, power grid operation is largely based on operators’ experience with very limited real-time decision support, resulting in inefficient operations.

The Graphical Contingency Analysis (GCA) tool is a visual analytic software tool that aids power grid operators and planners to effectively manage complex outage predictions and helps them predict potential network failures and take effective actions in response to adverse situations. Researchers developed the tool to provide effective decision support to grid operators and planners. Although the tool has not been deployed to utilities for daily use, it has been used in the North American Electric Reliability Corporation certified operator training classes to help operators and planners better understand contingencies and reach a contingency analysis solution faster than other tools allow today. This advantage can provide better grid reliability and save a significant of money for utilities.

Emergency Operations Management

Helping cities manage emergencies through social media

The City of Seattle’s Emergency Operations Center (EOC) is activated about eight times a year, typically due to weather-related events. During these crises, police, fire, city light (power), public utilities, the Department of Transportation, Mayor’s office, and emergency management personnel work to provide critical services and communicate with impacted citizens. The EOC may need to restore power, address road closures or severe accidents, or even supply food, water, and shelter.

Emergency managers desperately wanted to use social media as a source of “on the ground” intelligence, but the sheer volume of this data made it hard to sift through to find useful indicators of disruption or public need. Emergency personnel read social media sources manually—and in the Seattle region, there can be tens of thousands of Tweets per hour. With the help of the Scalable Reasoning System (SRS), the EOC was enabled to spend less time analyzing local reporting; SRS gives them at-a-glance situation awareness so that they can determine what issues the public is talking about, and where. With SRS, they will no longer have to comb through this data by hand; the system automatically aggregates streaming social media data into key themes and trends, which it presents visually.

Patent Search

Enabling quick, simple, and unique searches among over 16,000 patents

Scouring through tens of thousands of patents has never been described as easy or simple. Because patent searches are performed used keyword searches, users are constantly faced with terms that produce far too many results to navigate, or so few that the best results are left out. Without a high degree of familiarity with a subject, it often proves impossible to find those perfect keywords.

These problems led the U.S. Department of Energy to enlist the help of PNNL technologies, IN-SPIRE and the Scalable Reasoning System (SRS). Using these software applications, tiered categories were created. Specific technology areas are then clustered together through the identification of word occurrence patterns across all patent records. The result of these software applications ensures a quick and simple patent search that goes far beyond keywords, making this process much easier for the public, entrepreneurs, investors, and others.

Energy Efficiency

Energy improvements to maximize lifecycle savings

Meeting energy efficiency goals is important to many in order to maximize lifecycle savings. However, determining how to best meet these goals can be a challenge when you must consider the cost performance of heating, cooling, ventilation, lighting, motors, plug loads, refrigeration, building shell, and hot water systems.

The United States Army used the PNNL-developed Facility Energy Decision System (FEDS) to do just this. Upon analysis of over 40 Army sites, more than $340 million worth of lifecycle cost effective energy efficiency projects were identified with a projected average savings of 302,000 MMBTU per year. This equates to an average energy use intensity reduction of 27%.

Transportation Risk Reduction

Mass transportation plays a crucial role in the solution set to the nation’s economic, energy, and environmental challenges. Often times though, some of the largest transportation systems face the greatest security risks. Such is the case with the nation’s largest and highest-risk ferry system in Washington State.

The Washington State Ferry System and Washington State Patrol use PNNL’s Risk Reduction and Resource Assessment Model (3RAM) in order to estimate risk across the entire ferry system. The tool analyzes patterns of operation and usage, then provides appropriate deployment plans for resources such as canine teams and law enforcement officers. This technology has resulted in a significant reduction in mass transportation risk for the Washington State Ferry System. The U.S. Coast Guard has also approved this tool for operational use.